Navigating Through AI: The Test Manager's Guide to Staying Relevant
Gen AI and LLM topics are currently on heavy rotation and the IT domain is experiencing highs and lows of excitement regarding performance breakthroughs and fears that software engineers will be replaced by prompts tomorrow. Their concerns are not unreasonable—we can think of code development as language-to-language transformation, but what about the project governance and the managers who were shaping it? Where do they fit in the new AI-based IT world? As a Head of European Quality Engineering Practice in a global company with 50K+ employees, Maryna will share her experiences in dealing with various findings and challenges during AI enablement on projects, with a focus on quality and testing. You will learn: how to adapt your test management activities to AI reality, how to train your team with new skills, how to set the expectations and roadmap for transformations correctly, what will boost your performance, and what traps you may be caught in.
Maryna Didkovska serves as the Quality Engineering Director at EPAM Systems. In her roles spanning Test Manager, Delivery Manager, and Software Automation Engineer, she has adeptly led teams, establishing scalable testing procedures for extensive projects involving over 600 participants. Her expertise extends to crafting testing ecosystems at the enterprise scale, addressing quality architectural issues, and mentoring individuals towards becoming domain experts and leaders. Holding a PhD in Software Reliability, Maryna bridges her academic insights with her pragmatic experience in software automation testing and programming. This synergy enables her to collaborate effectively with global teams and clients, fostering persistent advancements in software quality and catalyzing digital transformations. A frequent contributor to technical and managerial conferences, such as STAREAST, SEETEST, EUROSTAR, Compass, etc; Maryna delves into a spectrum of testing subjects. She ardently champions transparent and measurable quality enhancement processes.